Reference images of a patient may be used to indicate the position of a target region of the patient during a radiation treatment procedure. For convenience, the term “radiation treatment” is used herein to mean radiosurgery and/or radiotherapy unless otherwise noted. Tracking of the treatment target increases the accuracy of the radiation treatment procedure so that irradiation of the healthy tissue surrounding the targeted region may be minimized.
A workflow to provide the radiation treatment to a patient may involve multiple stages corresponding to treatment planning, patient setup, and treatment delivery as described with regards to FIG. 1. As shown, the method 100 may begin with the treatment planning as a first stage to provide radiation treatment to the patient (block 110). The treatment planning stage may be initiated by obtaining of pre-treatment diagnostic images with one or more imaging modalities (e.g., CT image, MR image, etc.) of a volume of interest (VOI) of the patient. The treatment planning stage may further include identifying one or more reference points in one or more of the pre-treatment images. The reference points may be one or more imageable landmarks or points of interest in the acquired images that can be tracked during later stages discussed below. The acquired images in the treatment planning stage such as a CT image includes a pathological anatomy that is targeted for treatment, and well as a critical region(s) that is positioned near the pathological anatomy. Treatment planning software enables the generation of a critical region contour around the critical region and a target region contour around the pathological anatomy. Conventionally, a user manually delineates or uses a software tool to auto-delineate points on a display that is used by the treatment planning software to generate the corresponding contours. After the target has been defined, the critical and soft tissue volumes have been specified, and minimum radiation dose to the target and the maximum dose to normal and critical healthy tissue has been specified, the treatment planning software then produces a treatment plan, relying on the positional capabilities of the radiation treatment system.
The method 100 may subsequently include a patient setup as a second stage of the workflow before providing the radiation treatment to the patient (block 120). A stereo image may be generated, such as by X-ray imaging, or a 3D alignment image may be generated, such as a cone-beam CT (CBCT) or a megavoltage CT (MVCT) image, and then correlated to the preoperative image in order to locate the target region accurately. Then, a radiation source located on treatment delivery system is automatically positioned based on the correlation between the preoperative image and the stereo images (or 3D alignment image) in order to accurately target the desired treatment region in the patient. If the patient is not within the desired range of the radiation treatment delivery system, the position of the patient adjusted during the patient setup stage.
After the patient setup stage, treatment delivery may be performed on the patient based on the treatment plan (block 130). The images(s) taken during the patient set up stage may be used as a delivery reference for later registration. During treatment delivery, dynamic tracking of the target may be performed based on the use of x-ray images taken to identify internal features in the patient and external markers to track motions of the target due to, for example, patient respiration, with the registration results between a digitally reconstructed radiograph (DRR) and each of the live x-ray images used to generate a correlation model. The external markers may be light emitting diodes (LEDs) that are coupled to the patient and a tracker or motion detection system to track the position of one or more of the external markers. An example of one such system is the Synchrony™ respiratory tracking system developed by Accuray, Inc. However, other respiratory tracking systems may be used. After the correlation model is generated, the position measurements of the external markers may be used to compute the corresponding location of the target by using the correlation model. Once the location of the target (e.g., the tumor) has been computed, the radiation beam source position of the radiation treatment delivery system may be adjusted to compensate for the dynamic motion of the target due to patient respiration (or other movement). The radiation treatment delivery system may then deliver the dose of radiation to the tracked target in accordance with the radiation treatment plan developed during the treatment planning stage.
Thus, a sequence of x-ray images of a patient may be acquired and a correspondence between a location of a tumor of the patient and the motion of the patient as represented by LED markers that are placed on the patient's body may be determined. After the model has been generated, the motion of the LED markers may be used to predict the location of the tumor. Such information may be used to dynamically update the delivery of the radiation treatment from the radiation treatment equipment to the patient so that the target is irradiated according to the treatment plan, even as the location of the target moves based on the motion of the patient.
The x-ray images may be obtained based on sequential acquisition of the x-ray images of the patient. Each x-ray image may be correlated with a DRR image as it is acquired and a determination may be made as to whether the correlation results of the x-ray image satisfy correlation criteria. If the x-ray image satisfies the correlation criteria, then the x-ray image may be used in the building of the correlation model. However, if the x-ray image doesn't satisfy the correlation criteria, then the correlation parameters of the x-ray image may be modified or the x-ray image may not be used in the building of the correlation model. Subsequently, another x-ray image may be acquired and the process may repeat. Thus, a user viewing the acquired x-ray images that are used to build the correlation model may only view or modify the most recently acquired x-ray image.
Furthermore, when viewing the most recently acquired x-ray image that has been used to build the correlation model, the visibility of a tumor within the x-ray image may be difficult when separately viewing the most recently acquired x-ray image. For example, to a user reviewing a single x-ray image, the boundaries, shape, and size of the tumor may be difficult to identify.